Principal Data Science Architect

$182,400 - $220,000/Yr

Albertsons - Pleasanton, CA

posted 4 months ago

Full-time - Principal
Remote - Pleasanton, CA
10,001+ employees
Food and Beverage Retailers

About the position

The Principal Data Science Architect will be a key technical leader responsible for designing and implementing the data science architecture that underpins our AI and ML modeling capabilities and integration with applications and data pipelines. This person will scale multiple data science models to retail platforms. This role demands a visionary thinker with deep technical expertise and a strategic mindset, who can drive the evolution of our data science infrastructure and methodologies. The position will be based in Pleasanton, CA, one of our main regional offices, which include Seattle, WA, Portland, OR, Denver, CO, Dallas, TX, Chicago, IL, or Fullerton, CA, and Phoenix, AZ. In this role, you will define and implement the overarching data science architecture and strategy, ensuring the scalability, performance, and reliability of data science solutions. You will lead the selection and integration of data science tools, frameworks, and platforms, and build and deploy data science solutions at scale. You will also design and develop advanced machine learning and statistical models, oversee their deployment into production environments, and ensure best practices in data engineering, model management, and version control. Collaboration is key, as you will work closely with data engineers, data scientists, and software engineers to build and maintain robust data pipelines. You will provide technical mentorship and guidance to the data science team and collaborate with cross-functional teams to translate business requirements into scalable data science solutions. Staying abreast of the latest advancements in data science, machine learning, and AI technologies is essential, as you will evaluate and implement new tools and technologies to enhance the data science architecture. Additionally, you will establish and enforce data science best practices, including coding standards, documentation, and model validation, while ensuring data security and compliance with relevant regulations and standards. Developing and maintaining comprehensive documentation of the data science architecture and processes will also be part of your responsibilities.

Responsibilities

  • Define and implement the overarching data science architecture and strategy.
  • Ensure the scalability, performance, and reliability of data science solutions.
  • Lead the selection and integration of data science tools, frameworks, and platforms.
  • Build and deploy data science solutions at scale.
  • Design and develop advanced machine learning and statistical models.
  • Oversee the deployment of data science models into production environments.
  • Ensure best practices in data engineering, model management, and version control.
  • Work closely with data engineers, data scientists, and software engineers to build and maintain robust data pipelines.
  • Provide technical mentorship and guidance to the data science team.
  • Collaborate with cross-functional teams to translate business requirements into scalable data science solutions.
  • Stay abreast of the latest advancements in data science, machine learning, and AI technologies.
  • Evaluate and implement new tools and technologies to enhance the data science architecture.
  • Drive innovation through research, experimentation, and prototyping.
  • Establish and enforce data science best practices, including coding standards, documentation, and model validation.
  • Ensure data security and compliance with relevant regulations and standards.
  • Develop and maintain comprehensive documentation of the data science architecture and processes.

Requirements

  • 10+ years of experience in data science, with significant experience in architecting and deploying data science solutions at scale.
  • Proven track record of leading and managing data science projects and teams.
  • Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and data analysis tools (e.g., Python, R).
  • Strong background in data engineering and big data technologies (e.g., Hadoop, Spark).
  • Proficiency in SQL and experience with cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and presentation skills.
  • Ability to manage multiple projects and prioritize tasks effectively.
  • Product mindset and systems thinking.
  • Advanced degree in a STEM field like CS, DS, Engineering, Statistics, Math, etc. is preferred, or equivalent experience from building large scale solutions.

Nice-to-haves

  • Experience in retail industry.
  • High performance computing background and experience engaging with the engineering teams in a product model.
  • Knowledge of data visualization tools (e.g., Tableau, Power BI).
  • Familiarity with DevOps practices and tools for model deployment and monitoring (e.g., Docker, Kubernetes).
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